"tests/python/common/test_heterograph.py" did not exist on "c13903bf647e286879fba4f04cf3d8cdc0dc8ce7"
Commit 939ee964 authored by rusty1s's avatar rusty1s
Browse files

add workflows

parent 4d86558a
name: Building Wheels
on: [workflow_dispatch]
jobs:
wheel:
runs-on: ${{ matrix.os }}
strategy:
fail-fast: false
matrix:
os: [ubuntu-18.04, macos-10.15, windows-latest]
python-version: [3.6, 3.7, 3.8, 3.9]
torch-version: [1.8.0, 1.9.0]
cuda-version: ['cpu', 'cu101', 'cu102', 'cu111']
exclude:
- torch-version: 1.9.0
cuda-version: 'cu101'
- os: macos-10.15
cuda-version: 'cu101'
- os: macos-10.15
cuda-version: 'cu102'
- os: macos-10.15
cuda-version: 'cu111'
- os: windows-latest
cuda-version: 'cu101'
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- name: Update pip
run: |
pip install --upgrade pip
- name: Install CUDA ${{ matrix.cuda-version }}
if: ${{ matrix.cuda-version != 'cpu' }}
run: |
bash .github/workflows/cuda/${{ matrix.cuda-version }}-${{ runner.os }}.sh
- name: Install PyTorch ${{ matrix.torch-version }}+${{ matrix.cuda-version }}
run: |
pip install numpy typing-extensions dataclasses
pip install --no-index --no-cache-dir torch==${{ matrix.torch-version}} -f https://download.pytorch.org/whl/${{ matrix.cuda-version }}/torch_stable.html
python -c "import torch; print('PyTorch:', torch.__version__)"
python -c "import torch; print('CUDA:', torch.version.cuda)"
- name: Install main package for CPU
if: ${{ matrix.cuda-version == 'cpu' }}
run: |
FORCE_ONLY_CPU=1 pip install -e .
shell:
bash
- name: Install main package for GPU
if: ${{ matrix.cuda-version != 'cpu' }}
run: |
source .github/workflows/cuda/${{ matrix.cuda-version }}-${{ runner.os }}-env.sh
FORCE_CUDA=1 pip install -e .
shell:
bash
- name: Build wheel
run: |
pip install wheel
python setup.py bdist_wheel --dist-dir=dist
- name: Configure AWS
uses: aws-actions/configure-aws-credentials@v1
with:
aws-access-key-id: ${{ secrets.AWS_KEY_ID }}
aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
aws-region: us-east-1
- name: Upload wheel
run: |
aws s3 sync dist s3://pytorch-geometric.com/whl/torch-${{ matrix.torch-version }}+${{ matrix.cuda-version }} --grants read=uri=http://acs.amazonaws.com/groups/global/AllUsers
#!/bin/bash
CUDA_HOME=/usr/local/cuda-10.1
LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
PATH=${CUDA_HOME}/bin:${PATH}
#!/bin/bash
wget -nv https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget -nv https://developer.download.nvidia.com/compute/cuda/10.1/Prod/local_installers/cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb
sudo apt-key add /var/cuda-repo-10-1-local-10.1.243-418.87.00/7fa2af80.pub
sudo apt-get -qq update
sudo apt install cuda-nvcc-10-1 cuda-libraries-dev-10-1
sudo apt clean
rm -f https://developer.download.nvidia.com/compute/cuda/10.1/Prod/local_installers/cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb
#!/bin/bash
CUDA_HOME=/c/Program\ Files/NVIDIA\ GPU\ Computing\ Toolkit/CUDA/v10.1
PATH=${CUDA_HOME}/bin:$PATH
PATH=/c/Program\ Files\ \(x86\)/Microsoft\ Visual\ Studio/2017/BuildTools/MSBuild/15.0/Bin:$PATH
#!/bin/bash
# Install NVIDIA drivers, see:
# https://github.com/pytorch/vision/blob/master/packaging/windows/internal/cuda_install.bat#L99-L102
curl -k -L "https://drive.google.com/u/0/uc?id=1injUyo3lnarMgWyRcXqKg4UGnN0ysmuq&export=download" --output "/tmp/gpu_driver_dlls.zip"
7z x "/tmp/gpu_driver_dlls.zip" -o"/c/Windows/System32"
export CUDA_SHORT=10.1
export CUDA_URL=https://developer.download.nvidia.com/compute/cuda/${CUDA_SHORT}/Prod/local_installers/
export CUDA_FILE=cuda_${CUDA_SHORT}.243_426.00_win10.exe
# Install CUDA:
curl -k -L "${CUDA_URL}/${CUDA_FILE}" --output "${CUDA_FILE}"
echo ""
echo "Installing from ${CUDA_FILE}..."
PowerShell -Command "Start-Process -FilePath \"${CUDA_FILE}\" -ArgumentList \"-s nvcc_${CUDA_SHORT} cuobjdump_${CUDA_SHORT} nvprune_${CUDA_SHORT} cupti_${CUDA_SHORT} cublas_dev_${CUDA_SHORT} cudart_${CUDA_SHORT} cufft_dev_${CUDA_SHORT} curand_dev_${CUDA_SHORT} cusolver_dev_${CUDA_SHORT} cusparse_dev_${CUDA_SHORT} npp_dev_${CUDA_SHORT} nvrtc_dev_${CUDA_SHORT} nvml_dev_${CUDA_SHORT}\" -Wait -NoNewWindow"
echo "Done!"
rm -f "${CUDA_FILE}"
#!/bin/bash
CUDA_HOME=/usr/local/cuda-10.2
LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
PATH=${CUDA_HOME}/bin:${PATH}
#!/bin/bash
wget -nv https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget -nv https://developer.download.nvidia.com/compute/cuda/10.2/Prod/local_installers/cuda-repo-ubuntu1804-10-2-local-10.2.89-440.33.01_1.0-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu1804-10-2-local-10.2.89-440.33.01_1.0-1_amd64.deb
sudo apt-key add /var/cuda-repo-10-2-local-10.2.89-440.33.01/7fa2af80.pub
sudo apt-get -qq update
sudo apt install cuda-nvcc-10-2 cuda-libraries-dev-10-2
sudo apt clean
rm -f https://developer.download.nvidia.com/compute/cuda/10.2/Prod/local_installers/cuda-repo-ubuntu1804-10-2-local-10.2.89-440.33.01_1.0-1_amd64.deb
#!/bin/bash
CUDA_HOME=/c/Program\ Files/NVIDIA\ GPU\ Computing\ Toolkit/CUDA/v10.2
PATH=${CUDA_HOME}/bin:$PATH
PATH=/c/Program\ Files\ \(x86\)/Microsoft\ Visual\ Studio/2017/BuildTools/MSBuild/15.0/Bin:$PATH
#!/bin/bash
# Install NVIDIA drivers, see:
# https://github.com/pytorch/vision/blob/master/packaging/windows/internal/cuda_install.bat#L99-L102
curl -k -L "https://drive.google.com/u/0/uc?id=1injUyo3lnarMgWyRcXqKg4UGnN0ysmuq&export=download" --output "/tmp/gpu_driver_dlls.zip"
7z x "/tmp/gpu_driver_dlls.zip" -o"/c/Windows/System32"
export CUDA_SHORT=10.2
export CUDA_URL=https://developer.download.nvidia.com/compute/cuda/${CUDA_SHORT}/Prod/local_installers
export CUDA_FILE=cuda_${CUDA_SHORT}.89_441.22_win10.exe
# Install CUDA:
curl -k -L "${CUDA_URL}/${CUDA_FILE}" --output "${CUDA_FILE}"
echo ""
echo "Installing from ${CUDA_FILE}..."
PowerShell -Command "Start-Process -FilePath \"${CUDA_FILE}\" -ArgumentList \"-s nvcc_${CUDA_SHORT} cuobjdump_${CUDA_SHORT} nvprune_${CUDA_SHORT} cupti_${CUDA_SHORT} cublas_dev_${CUDA_SHORT} cudart_${CUDA_SHORT} cufft_dev_${CUDA_SHORT} curand_dev_${CUDA_SHORT} cusolver_dev_${CUDA_SHORT} cusparse_dev_${CUDA_SHORT} npp_dev_${CUDA_SHORT} nvrtc_dev_${CUDA_SHORT} nvml_dev_${CUDA_SHORT}\" -Wait -NoNewWindow"
echo "Done!"
rm -f "${CUDA_FILE}"
#!/bin/bash
CUDA_HOME=/usr/local/cuda-11.1
LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
PATH=${CUDA_HOME}/bin:${PATH}
#!/bin/bash
wget -nv https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget -nv https://developer.download.nvidia.com/compute/cuda/11.1.1/local_installers/cuda-repo-ubuntu1804-11-1-local_11.1.1-455.32.00-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu1804-11-1-local_11.1.1-455.32.00-1_amd64.deb
sudo apt-key add /var/cuda-repo-ubuntu1804-11-1-local/7fa2af80.pub
sudo apt-get -qq update
sudo apt install cuda-nvcc-11-1 cuda-libraries-dev-11-1
sudo apt clean
rm -f https://developer.download.nvidia.com/compute/cuda/11.1.1/local_installers/cuda-repo-ubuntu1804-11-1-local_11.1.1-455.32.00-1_amd64.deb
#!/bin/bash
CUDA_HOME=/c/Program\ Files/NVIDIA\ GPU\ Computing\ Toolkit/CUDA/v11.1
PATH=${CUDA_HOME}/bin:$PATH
PATH=/c/Program\ Files\ \(x86\)/Microsoft\ Visual\ Studio/2017/BuildTools/MSBuild/15.0/Bin:$PATH
#!/bin/bash
# Install NVIDIA drivers, see:
# https://github.com/pytorch/vision/blob/master/packaging/windows/internal/cuda_install.bat#L99-L102
curl -k -L "https://drive.google.com/u/0/uc?id=1injUyo3lnarMgWyRcXqKg4UGnN0ysmuq&export=download" --output "/tmp/gpu_driver_dlls.zip"
7z x "/tmp/gpu_driver_dlls.zip" -o"/c/Windows/System32"
export CUDA_SHORT=11.1
export CUDA_URL=https://developer.download.nvidia.com/compute/cuda/${CUDA_SHORT}.1/local_installers
export CUDA_FILE=cuda_${CUDA_SHORT}.1_456.81_win10.exe
# Install CUDA:
curl -k -L "${CUDA_URL}/${CUDA_FILE}" --output "${CUDA_FILE}"
echo ""
echo "Installing from ${CUDA_FILE}..."
PowerShell -Command "Start-Process -FilePath \"${CUDA_FILE}\" -ArgumentList \"-s nvcc_${CUDA_SHORT} cuobjdump_${CUDA_SHORT} nvprune_${CUDA_SHORT} cupti_${CUDA_SHORT} cublas_dev_${CUDA_SHORT} cudart_${CUDA_SHORT} cufft_dev_${CUDA_SHORT} curand_dev_${CUDA_SHORT} cusolver_dev_${CUDA_SHORT} cusparse_dev_${CUDA_SHORT} npp_dev_${CUDA_SHORT} nvrtc_dev_${CUDA_SHORT} nvml_dev_${CUDA_SHORT}\" -Wait -NoNewWindow"
echo "Done!"
rm -f "${CUDA_FILE}"
name: Linting
on: [push, pull_request]
jobs:
flake8:
runs-on: ${{ matrix.os }}
strategy:
matrix:
os: [ubuntu-latest]
python-version: [3.6]
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- name: Install dependencies
run: |
pip install flake8
- name: Run linting
run: |
flake8 .
name: Testing
on: [push, pull_request]
jobs:
pytest:
runs-on: ${{ matrix.os }}
strategy:
matrix:
os: [ubuntu-latest, windows-latest]
python-version: [3.6]
torch-version: [1.8.0, 1.9.0]
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- name: Update pip
run: |
pip install --upgrade pip
- name: Install PyTorch ${{ matrix.torch-version }}
run: |
pip install torch==${{ matrix.torch-version}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
- name: Install main package
run: |
pip install -e .[test]
- name: Run test-suite
run: |
python setup.py test
- name: Generate coverage report
if: success()
run: |
pip install coverage
coverage xml
- name: Upload coverage report to codecov
uses: codecov/codecov-action@v1
if: success()
with:
file: coverage.xml
language: shell
os:
- linux
- osx
- windows
env:
global:
- CUDA_HOME=/usr/local/cuda
jobs:
# Python 3.6
- PYTHON_VERSION=3.6 TORCH_VERSION=1.8.0 IDX=cpu
- PYTHON_VERSION=3.6 TORCH_VERSION=1.8.0 IDX=cu101
- PYTHON_VERSION=3.6 TORCH_VERSION=1.8.0 IDX=cu102
- PYTHON_VERSION=3.6 TORCH_VERSION=1.8.0 IDX=cu111
- PYTHON_VERSION=3.6 TORCH_VERSION=1.7.0 IDX=cpu
- PYTHON_VERSION=3.6 TORCH_VERSION=1.7.0 IDX=cu92
- PYTHON_VERSION=3.6 TORCH_VERSION=1.7.0 IDX=cu101
- PYTHON_VERSION=3.6 TORCH_VERSION=1.7.0 IDX=cu102
- PYTHON_VERSION=3.6 TORCH_VERSION=1.7.0 IDX=cu110
# Python 3.7
- PYTHON_VERSION=3.7 TORCH_VERSION=1.8.0 IDX=cpu
- PYTHON_VERSION=3.7 TORCH_VERSION=1.8.0 IDX=cu101
- PYTHON_VERSION=3.7 TORCH_VERSION=1.8.0 IDX=cu102
- PYTHON_VERSION=3.7 TORCH_VERSION=1.8.0 IDX=cu111
- PYTHON_VERSION=3.7 TORCH_VERSION=1.7.0 IDX=cpu
- PYTHON_VERSION=3.7 TORCH_VERSION=1.7.0 IDX=cu92
- PYTHON_VERSION=3.7 TORCH_VERSION=1.7.0 IDX=cu101
- PYTHON_VERSION=3.7 TORCH_VERSION=1.7.0 IDX=cu102
- PYTHON_VERSION=3.7 TORCH_VERSION=1.7.0 IDX=cu110
# Python 3.8
- PYTHON_VERSION=3.8 TORCH_VERSION=1.8.0 IDX=cpu
- PYTHON_VERSION=3.8 TORCH_VERSION=1.8.0 IDX=cu101
- PYTHON_VERSION=3.8 TORCH_VERSION=1.8.0 IDX=cu102
- PYTHON_VERSION=3.8 TORCH_VERSION=1.8.0 IDX=cu111
- PYTHON_VERSION=3.8 TORCH_VERSION=1.7.0 IDX=cpu
- PYTHON_VERSION=3.8 TORCH_VERSION=1.7.0 IDX=cu92
- PYTHON_VERSION=3.8 TORCH_VERSION=1.7.0 IDX=cu101
- PYTHON_VERSION=3.8 TORCH_VERSION=1.7.0 IDX=cu102
- PYTHON_VERSION=3.8 TORCH_VERSION=1.7.0 IDX=cu110
jobs:
# For daily builds, we only test on Python 3.6 with 11.0/11.1.
# For deployment, we exclude *all* macOS CUDA and Windows CUDA 9.2 jobs.
exclude:
# Python 3.6 / PyTorch 1.8.0
- if: not (tag is present or commit_message =~ ci-deploy) and os != osx
env: PYTHON_VERSION=3.6 TORCH_VERSION=1.8.0 IDX=cpu
- if: not (tag is present or commit_message =~ ci-deploy) or os = osx
env: PYTHON_VERSION=3.6 TORCH_VERSION=1.8.0 IDX=cu101
- if: not (tag is present or commit_message =~ ci-deploy) or os = osx
env: PYTHON_VERSION=3.6 TORCH_VERSION=1.8.0 IDX=cu102
- if: os = osx
env: PYTHON_VERSION=3.6 TORCH_VERSION=1.8.0 IDX=cu111
# Python 3.6 / PyTorch 1.7.0
- if: not (tag is present or commit_message =~ ci-deploy) and os != osx
env: PYTHON_VERSION=3.6 TORCH_VERSION=1.7.0 IDX=cpu
- if: not (tag is present or commit_message =~ ci-deploy) or os != linux
env: PYTHON_VERSION=3.6 TORCH_VERSION=1.7.0 IDX=cu92
- if: not (tag is present or commit_message =~ ci-deploy) or os = osx
env: PYTHON_VERSION=3.6 TORCH_VERSION=1.7.0 IDX=cu101
- if: not (tag is present or commit_message =~ ci-deploy) or os = osx
env: PYTHON_VERSION=3.6 TORCH_VERSION=1.7.0 IDX=cu102
- if: os = osx
env: PYTHON_VERSION=3.6 TORCH_VERSION=1.7.0 IDX=cu110
# Python 3.7 / PyTorch 1.8.0
- if: not (tag is present or commit_message =~ ci-deploy)
env: PYTHON_VERSION=3.7 TORCH_VERSION=1.8.0 IDX=cpu
- if: not (tag is present or commit_message =~ ci-deploy) or os = osx
env: PYTHON_VERSION=3.7 TORCH_VERSION=1.8.0 IDX=cu101
- if: not (tag is present or commit_message =~ ci-deploy) or os = osx
env: PYTHON_VERSION=3.7 TORCH_VERSION=1.8.0 IDX=cu102
- if: not (tag is present or commit_message =~ ci-deploy) or os = osx
env: PYTHON_VERSION=3.7 TORCH_VERSION=1.8.0 IDX=cu111
- if: not (tag is present or commit_message =~ ci-deploy)
# Python 3.7 / PyTorch 1.7.0
env: PYTHON_VERSION=3.7 TORCH_VERSION=1.7.0 IDX=cpu
- if: not (tag is present or commit_message =~ ci-deploy) or os != linux
env: PYTHON_VERSION=3.7 TORCH_VERSION=1.7.0 IDX=cu92
- if: not (tag is present or commit_message =~ ci-deploy) or os = osx
env: PYTHON_VERSION=3.7 TORCH_VERSION=1.7.0 IDX=cu101
- if: not (tag is present or commit_message =~ ci-deploy) or os = osx
env: PYTHON_VERSION=3.7 TORCH_VERSION=1.7.0 IDX=cu102
- if: not (tag is present or commit_message =~ ci-deploy) or os = osx
env: PYTHON_VERSION=3.7 TORCH_VERSION=1.7.0 IDX=cu110
# Python 3.8 / PyTorch 1.8.0
- if: not (tag is present or commit_message =~ ci-deploy)
env: PYTHON_VERSION=3.8 TORCH_VERSION=1.8.0 IDX=cpu
- if: not (tag is present or commit_message =~ ci-deploy) or os = osx
env: PYTHON_VERSION=3.8 TORCH_VERSION=1.8.0 IDX=cu101
- if: not (tag is present or commit_message =~ ci-deploy) or os = osx
env: PYTHON_VERSION=3.8 TORCH_VERSION=1.8.0 IDX=cu102
- if: not (tag is present or commit_message =~ ci-deploy) or os = osx
env: PYTHON_VERSION=3.8 TORCH_VERSION=1.8.0 IDX=cu111
- if: not (tag is present or commit_message =~ ci-deploy)
# Python 3.8 / PyTorch 1.7.0
env: PYTHON_VERSION=3.8 TORCH_VERSION=1.7.0 IDX=cpu
- if: not (tag is present or commit_message =~ ci-deploy) or os != linux
env: PYTHON_VERSION=3.8 TORCH_VERSION=1.7.0 IDX=cu92
- if: not (tag is present or commit_message =~ ci-deploy) or os = osx
env: PYTHON_VERSION=3.8 TORCH_VERSION=1.7.0 IDX=cu101
- if: not (tag is present or commit_message =~ ci-deploy) or os = osx
env: PYTHON_VERSION=3.8 TORCH_VERSION=1.7.0 IDX=cu102
- if: not (tag is present or commit_message =~ ci-deploy) or os = osx
env: PYTHON_VERSION=3.8 TORCH_VERSION=1.7.0 IDX=cu110
install:
- source script/gcc.sh
- source script/cuda.sh
- source script/conda.sh
- conda create --yes -n test python="${PYTHON_VERSION}"
- source activate test
- conda install pytorch=${TORCH_VERSION} ${TOOLKIT} -c pytorch -c conda-forge --yes
- source script/torch.sh
- pip install flake8
- pip install codecov
- pip install -e .[test]
script:
- flake8 .
- python setup.py test
after_success:
- python setup.py bdist_wheel --dist-dir=dist
- ls -lah dist/
- codecov
deploy:
provider: s3
region: eu-central-1
edge: true
access_key_id: ${S3_ACCESS_KEY}
secret_access_key: ${S3_SECRET_ACCESS_KEY}
bucket: pytorch-geometric.com
local_dir: dist
upload_dir: whl/torch-${TORCH_VERSION}+${IDX}
acl: public_read
on:
all_branches: true
repo: rusty1s/pytorch_spline_conv
condition: $TRAVIS_TAG != "" || $TRAVIS_COMMIT_MESSAGE =~ ci-deploy
notifications:
email: false
#!/bin/bash
if [ "${TRAVIS_OS_NAME}" = "linux" ]; then
wget -nv https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh
chmod +x miniconda.sh
./miniconda.sh -b
PATH=/home/travis/miniconda3/bin:${PATH}
fi
if [ "${TRAVIS_OS_NAME}" = "osx" ]; then
wget -nv https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh -O miniconda.sh
chmod +x miniconda.sh
./miniconda.sh -b
PATH=/Users/travis/miniconda3/bin:${PATH}
fi
if [ "${TRAVIS_OS_NAME}" = "windows" ]; then
choco install openssl.light
choco install miniconda3
PATH=/c/tools/miniconda3/Scripts:$PATH
fi
conda update --yes conda
conda create --yes -n test python="${PYTHON_VERSION}"
#!/bin/bash
if [ "${TRAVIS_OS_NAME}" = "linux" ] && [ "$IDX" = "cpu" ]; then
export TOOLKIT=cpuonly
fi
if [ "${TRAVIS_OS_NAME}" = "linux" ] && [ "$IDX" = "cu92" ]; then
export CUDA_SHORT=9.2
export CUDA=9.2.148-1
export UBUNTU_VERSION=ubuntu1604
export TOOLKIT="cudatoolkit=${CUDA_SHORT}"
fi
if [ "${TRAVIS_OS_NAME}" = "linux" ] && [ "$IDX" = "cu101" ]; then
export IDX=cu101
export CUDA_SHORT=10.1
export CUDA=10.1.243-1
export UBUNTU_VERSION=ubuntu1804
export TOOLKIT="cudatoolkit=${CUDA_SHORT}"
fi
if [ "${TRAVIS_OS_NAME}" = "linux" ] && [ "$IDX" = "cu102" ]; then
export CUDA_SHORT=10.2
export CUDA=10.2.89-1
export UBUNTU_VERSION=ubuntu1804
export TOOLKIT="cudatoolkit=${CUDA_SHORT}"
fi
if [ "${TRAVIS_OS_NAME}" = "linux" ] && [ "$IDX" = "cu110" ]; then
export CUDA_SHORT=11.0
export TOOLKIT="cudatoolkit=${CUDA_SHORT}"
fi
if [ "${TRAVIS_OS_NAME}" = "linux" ] && [ "$IDX" = "cu111" ]; then
export CUDA_SHORT=11.1
export TOOLKIT="cudatoolkit=${CUDA_SHORT}"
fi
if [ "${TRAVIS_OS_NAME}" = "windows" ] && [ "$IDX" = "cpu" ]; then
export TOOLKIT=cpuonly
fi
if [ "${TRAVIS_OS_NAME}" = "windows" ] && [ "$IDX" = "cu92" ]; then
export CUDA_SHORT=9.2
export CUDA_URL=https://developer.nvidia.com/compute/cuda/${CUDA_SHORT}/Prod2/local_installers2
export CUDA_FILE=cuda_${CUDA_SHORT}.148_win10
export TOOLKIT="cudatoolkit=${CUDA_SHORT}"
fi
if [ "${TRAVIS_OS_NAME}" = "windows" ] && [ "$IDX" = "cu101" ]; then
export CUDA_SHORT=10.1
export CUDA_URL=https://developer.nvidia.com/compute/cuda/${CUDA_SHORT}/Prod/local_installers
export CUDA_FILE=cuda_${CUDA_SHORT}.105_418.96_win10.exe
export TOOLKIT="cudatoolkit=${CUDA_SHORT}"
fi
if [ "${TRAVIS_OS_NAME}" = "windows" ] && [ "$IDX" = "cu102" ]; then
export CUDA_SHORT=10.2
export CUDA_URL=https://developer.download.nvidia.com/compute/cuda/${CUDA_SHORT}/Prod/local_installers
export CUDA_FILE=cuda_${CUDA_SHORT}.89_441.22_win10.exe
export TOOLKIT="cudatoolkit=${CUDA_SHORT}"
fi
if [ "${TRAVIS_OS_NAME}" = "windows" ] && [ "$IDX" = "cu110" ]; then
export CUDA_SHORT=11.0
export CUDA_URL=https://developer.download.nvidia.com/compute/cuda/${CUDA_SHORT}.2/local_installers
export CUDA_FILE=cuda_${CUDA_SHORT}.2_451.48_win10.exe
export TOOLKIT="cudatoolkit=${CUDA_SHORT}"
fi
if [ "${TRAVIS_OS_NAME}" = "windows" ] && [ "$IDX" = "cu111" ]; then
export CUDA_SHORT=11.1
export CUDA_URL=https://developer.download.nvidia.com/compute/cuda/${CUDA_SHORT}.1/local_installers
export CUDA_FILE=cuda_${CUDA_SHORT}.1_456.81_win10.exe
export TOOLKIT="cudatoolkit=${CUDA_SHORT}"
fi
if [ "${TRAVIS_OS_NAME}" = "osx" ] && [ "$IDX" = "cpu" ]; then
export TOOLKIT=""
fi
if [ "${IDX}" = "cpu" ]; then
export FORCE_ONLY_CPU=1
else
export FORCE_CUDA=1
fi
if [ "${TRAVIS_OS_NAME}" = "linux" ] && { [ "${IDX}" = "cu92" ] || [ "${IDX}" = "cu101" ] || [ "${IDX}" = "cu102" ]; }; then
INSTALLER="cuda-repo-${UBUNTU_VERSION}_${CUDA}_amd64.deb"
wget -nv "http://developer.download.nvidia.com/compute/cuda/repos/${UBUNTU_VERSION}/x86_64/${INSTALLER}"
sudo dpkg -i "${INSTALLER}"
wget -nv "https://developer.download.nvidia.com/compute/cuda/repos/${UBUNTU_VERSION}/x86_64/7fa2af80.pub"
sudo apt-key add 7fa2af80.pub
sudo apt update -qq
sudo apt install "cuda-core-${CUDA_SHORT/./-}" "cuda-nvcc-${CUDA_SHORT/./-}" "cuda-libraries-dev-${CUDA_SHORT/./-}"
sudo apt clean
CUDA_HOME=/usr/local/cuda-${CUDA_SHORT}
LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
PATH=${CUDA_HOME}/bin:${PATH}
nvcc --version
# Fix cublas on CUDA 10.2:
if [ -d "/usr/local/cuda-10.2/targets/x86_64-linux/include" ]; then
sudo cp -r /usr/local/cuda-10.2/targets/x86_64-linux/include/* "${CUDA_HOME}/include/"
fi
if [ -d "/usr/local/cuda-10.2/targets/x86_64-linux/lib" ]; then
sudo cp -r /usr/local/cuda-10.2/targets/x86_64-linux/lib/* "${CUDA_HOME}/lib/"
fi
fi
if [ "${TRAVIS_OS_NAME}" = "linux" ] && [ "${IDX}" = "cu110" ]; then
wget -nv https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget -nv https://developer.download.nvidia.com/compute/cuda/11.0.3/local_installers/cuda-repo-ubuntu1804-11-0-local_11.0.3-450.51.06-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu1804-11-0-local_11.0.3-450.51.06-1_amd64.deb
sudo apt-key add /var/cuda-repo-ubuntu1804-11-0-local/7fa2af80.pub
sudo apt update -qq
sudo apt install cuda-nvcc-11-0 cuda-libraries-dev-11-0
sudo apt clean
CUDA_HOME=/usr/local/cuda-${CUDA_SHORT}
LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
PATH=${CUDA_HOME}/bin:${PATH}
nvcc --version
fi
if [ "${TRAVIS_OS_NAME}" = "linux" ] && [ "${IDX}" = "cu111" ]; then
wget -nv https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget -nv https://developer.download.nvidia.com/compute/cuda/11.1.1/local_installers/cuda-repo-ubuntu1804-11-1-local_11.1.1-455.32.00-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu1804-11-1-local_11.1.1-455.32.00-1_amd64.deb
sudo apt-key add /var/cuda-repo-ubuntu1804-11-1-local/7fa2af80.pub
sudo apt update -qq
sudo apt install cuda-nvcc-11-1 cuda-libraries-dev-11-1
sudo apt clean
CUDA_HOME=/usr/local/cuda-${CUDA_SHORT}
LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
PATH=${CUDA_HOME}/bin:${PATH}
nvcc --version
fi
if [ "${TRAVIS_OS_NAME}" = "windows" ] && [ "${IDX}" != "cpu" ]; then
# Install NVIDIA drivers, see:
# https://github.com/pytorch/vision/blob/master/packaging/windows/internal/cuda_install.bat#L99-L102
curl -k -L "https://drive.google.com/u/0/uc?id=1injUyo3lnarMgWyRcXqKg4UGnN0ysmuq&export=download" --output "/tmp/gpu_driver_dlls.zip"
7z x "/tmp/gpu_driver_dlls.zip" -o"/c/Windows/System32"
# Install CUDA:
wget -nv "${CUDA_URL}/${CUDA_FILE}"
PowerShell -Command "Start-Process -FilePath \"${CUDA_FILE}\" -ArgumentList \"-s nvcc_${CUDA_SHORT} cuobjdump_${CUDA_SHORT} nvprune_${CUDA_SHORT} cupti_${CUDA_SHORT} cublas_dev_${CUDA_SHORT} cudart_${CUDA_SHORT} cufft_dev_${CUDA_SHORT} curand_dev_${CUDA_SHORT} cusolver_dev_${CUDA_SHORT} cusparse_dev_${CUDA_SHORT} npp_dev_${CUDA_SHORT} nvrtc_dev_${CUDA_SHORT} nvml_dev_${CUDA_SHORT}\" -Wait -NoNewWindow"
CUDA_HOME=/c/Program\ Files/NVIDIA\ GPU\ Computing\ Toolkit/CUDA/v${CUDA_SHORT}
PATH=${CUDA_HOME}/bin:$PATH
PATH=/c/Program\ Files\ \(x86\)/Microsoft\ Visual\ Studio/2017/BuildTools/MSBuild/15.0/Bin:$PATH
nvcc --version
fi
#!/bin/bash
if [ "${TRAVIS_OS_NAME}" = "linux" ]; then
sudo add-apt-repository ppa:ubuntu-toolchain-r/test --yes
sudo apt update
sudo apt install gcc-7 g++-7 --yes
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-7 60 \
--slave /usr/bin/g++ g++ /usr/bin/g++-7
sudo update-alternatives --config gcc
gcc --version
g++ --version
fi
#!/bin/bash
# https://github.com/pytorch/pytorch/commit/d2e16dd888a9b5fd55bd475d4fcffb70f388d4f0
if [ "${TRAVIS_OS_NAME}" = "windows" ] && [ "${TORCH_VERSION}" = "1.7.0" ]; then
echo "Fix nvcc for PyTorch"
sed -i.bak -e 's/CONSTEXPR_EXCEPT_WIN_CUDA/const/g' /c/tools/miniconda3/envs/test/lib/site-packages/torch/include/torch/csrc/jit/api/module.h
sed -i.bak -e 's/return \*(this->value)/return \*((type\*)this->value)/g' /c/tools/miniconda3/envs/test/lib/site-packages/torch/include/pybind11/cast.h
fi
if [ "${TRAVIS_OS_NAME}" = "windows" ] && [ "${TORCH_VERSION}" = "1.7.0" ]; then
echo "Fix nvcc for PyTorch 1.7.0"
sed -i.bak '/static constexpr Symbol Kind/d' /c/tools/miniconda3/envs/test/lib/site-packages/torch/include/torch/csrc/jit/ir/ir.h
fi
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